Abstract Details

Title Predictors of Inaccurate Stroke Alerts in the Emergency Department

Topic Cerebrovascular Disease and Interventional Neurology

Presentation(s) P5 - Poster Session 5 (5:30 PM-6:30 PM)

Poster/Presentation
Number 5-017

Objective Evaluate predictors of inaccurate stroke alerts to improve utilization of resources and the quality of care provided.

Background Approximately 38% of stroke alerts activated in the emergency department (ED) annually at our academic comprehensive stroke center accurately identify a true stroke. A stroke alert activates a multidisciplinary team to allow for rapid triage and advanced imaging, but stroke mimics can result in high resource utilization, unnecessary exposure to radiation, delayed care of the underlying cause of symptoms, and burnout among providers.

Design/Methods A retrospective chart review was conducted of all stroke alerts activated in our ED between May 2022 and April 2023 to evaluate demographics and clinical characteristics. Accurate stroke was defined as a final diagnosis of either ischemic stroke, transient ischemic attack (TIA), or intracranial hemorrhage (ICH). Univariate and binomial logistic regression analyses were completed.

Results Among 1,537 patients (mean age 66 ± 17 years, 49% male), 41% were diagnosed with an accurate stroke (25% ischemic, 16% ICH, 1% TIA). Most common mimics were toxic/metabolic encephalopathy (33%), seizure (13%) and migraine (10%). Logistic regression showed predictors of stroke mimics were younger age, female gender, diabetes mellitus, prior stroke, prior or presenting seizure, sensory complaint, altered mental status, and dizziness. Stroke mimics were less likely to have atrial fibrillation, weakness, language deficit, intubation, systolic blood pressure over 160, or leukocytosis, and were more likely to present by personal vehicle than by emergency services (p<0.05). There were no differences in accuracy based on time of day or year.

Conclusions

A majority of ED stroke mimics were associated with specific presenting symptoms, particularly altered mental status, prior seizure, and dizziness. Focused education or use of triage scores that incorporate these findings can be tailored towards staff to reduce the frequency of inaccurate stroke alerts while maintaining a high positive predictive value.

Authors/Disclosures
Angelica N. Byrd (University of Florida College of Medicine) PRESENTER	Miss Byrd has nothing to disclose.
Daniel C. Mestre (UF College of Medicine)	Mr. Mestre has nothing to disclose.
Drashti R. Patel	Miss Patel has nothing to disclose.
Fahad Khan	No disclosure on file
Amita Singh, MD (University of Florida)	Dr. Singh has nothing to disclose.
Christina Wilson, MD, FAAN (University of Florida)	Dr. Wilson has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for NIH Stroke Net. The institution of an immediate family member of Dr. Wilson has received research support from NIH. The institution of Dr. Wilson has received research support from Bristol-Myers Squibb and BMS-Pfizer/Roche Diagnostics . An immediate family member of Dr. Wilson has received intellectual property interests from a discovery or technology relating to health care. Dr. Wilson has received publishing royalties from a publication relating to health care. Dr. Wilson has received publishing royalties from a publication relating to health care.

��ɫ��

��ɫ��